Estimating Position of Mobile Terminals with Survey Data
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stimating Position of Mobile Terminals with Survey Data Michael McGuire Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, ON M5S 3G4, Canada Email: [email protected]
Konstantinos N. Plataniotis Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, ON M5S 3G4, Canada Email: [email protected]
Anastasios N. Venetsanopoulos Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, ON M5S 3G4, Canada Email: [email protected] Received 30 July 2001 and in revised form 1 October 2001 Estimating the position of mobile terminals is an important problem for cellular networks. This paper describes low cost methods of locating mobile terminals in urban environments. These methods use data collected during propagation surveys of the network area. It will be shown how the maximum likelihood estimate and minimum mean-square error estimators can be approximated using survey data. Furthermore, the approximate solutions can provide low variance location estimates with low computational cost compared to other methods. Keywords and phrases: radio location, non-parametric methods, cellular radio networks.
1. INTRODUCTION The market for wireless networking services is undergoing fast growth. This growth is expected to continue with the proliferation of wireless data and digital multimedia devices. There are several reasons for a network provider to estimate the position of the mobile terminals in their network ranging from emergency communications to resource allocation. Assisting emergency communications is the most immediate concern of cellular network operators with millions of emergency 911 calls being made with cellular telephones every year in the U.S. alone [1]. The FCC in the United States has mandated that cellular network providers must be able to provide an estimated location of terminals making E911 calls that is accurate to within 100 meters for 67% of calls for network-based solutions [2, 3]. For proposed third and fourth generation cellular networks, it is envisioned that wireless networks will be required to provide higher bandwidth multimedia data with strict quality of service requirements [4]. It has been argued that one method to provide these services is to use mobile terminal
location and prediction to allocate resources to the terminals [5, 6]. Thus, mobile terminal location estimation will become an integral part of wireless network control systems. Several methods have been proposed in the literature for the location of mobile terminals in wireless networks based on Angle of Arrival (AoA), Time of Arrival (ToA), or Received Signal Strength (RSS) measurements [7, 8]. Other options explored in the literature include adding GPS receiver hardware to the mobile terminals [9]. GPS can offer very high precision geo-location. This technology has the disadvantage that the mobile terminals
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